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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

PhotoSketch: a photocentric urban 3D modeling system

Online mapping services from Google, Apple, and Microsoft are exceedingly popular applications for exploring 3D urban cities. Their explosive growth provides impetus for photorealistic 3D modeling of urban scenes. Although classical algorithms such as multiview stereo and laser range scanners are traditional sources for detailed 3D models of existing structures, they generate heavyweight models that are not appropriate for the streaming data that these navigation applications leverage. Instead, lightweight models as produced by interactive image-based tools are better suited for this domain. The contribution of this work is that it merges the benefits of multiview geometry, an intuitive sketching interface, and dynamic texture mapping to produce lightweight photorealistic 3D models of buildings. We present experimental results from urban scenes using our PhotoSketch system.

3D photography↗
DOE OSTI2019

Performance investigation of high-speed FSO transmission system under the influence of different atmospheric conditions incorporating 3-D orthogonal modulation scheme

In this paper, we report the modeling and simulative investigation of a free space optics (FSO) transmission system using non-return to zero/differential quadrature phase shift keying/polarization shift keying 3-D orthogonal modulation scheme in which three independent 40 Gb/s data streams are transmitted simultaneously using different signal parameters over the same channel to improve the spectral efficiency of the link. The proposed system demonstrates a successful transmission of 120 Gb/s information over an FSO link range of 25 km with an acceptable bit-error rate (∼10{sup −9}) under clear weather conditions. The performance of the proposed link is also analyzed under the effect of atmospheric turbulence. Further, we compare the performance of the proposed system with previously reported works in the literature and the results demonstrate that the proposed 3-D orthogonal modulation scheme based FSO transmission system performs better in terms of spectral efficiency, information capacity and maximum achievable link distance.

42 ENGINEERING↗
DOE OSTI2024

In-situ qualification and physics-based process design for aerosol jet printing via spatially correlated light scattering measurements

Aerosol jet printing is a contactless, digital, and additive technique broadly used for manufacturing flexible, hybrid, and conformal electronics. However, batch-to-batch variability has hindered widespread industry adoption and scaling to production volumes. Recently, light scattering measurements have emerged as a tool to measure aerosol volume fraction – a key parameter determining deposition rate – and have proven an effective feedback source for closed loop control on timescales ranging from minutes to hours. Here, the efficacy of light scattering measurements as a tool for in-situ qualification over shorter time durations is explored. To be the linear relationship between light scattering measurements and deposition rate was validated at 500 ms time intervals, allowing deposition rate to be mapped to positional coordinates and providing a new data stream to drive quality control assessments. Because light scattering measurements are indicative of a physical process parameter, they were substituted into equations for resistance and sheet resistance, resulting in predictions nominally within 10% of measured values for sets of printed devices. Finally, to highlight a more active utility, light scattering measurements were employed in a print repair framework, successfully repairing prints with randomly induced defects to within 5% of the measured resistance of a control set.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Spinning the digital thread with hybrid manufacturing

Integrated process monitoring and feedback capabilities for hybrid manufacturing have shown potential as a test platform for the development and implementation of the digital thread. Additionally, hybrid manufacturing alleviates the implementation of the digital thread as fewer systems are involved for a broader base of manufacturing operations. Researchers have developed coordinated process monitoring architectures to capture and leverage various existing data streams in the hybrid manufacturing process and improve the quality of manufactured components. This work is fundamentally different because it shows how common communication structures that exist on any commercial CNC can be used to enhance CNC based manufacturing processes.

42 ENGINEERING↗
DOE OSTI2025

A virtual Frisch-grid geometry-based CZT gamma detector for in-field radioisotope identification

Here, we present a Virtual Frisch-Grid geometry-based CZT gamma detector developed for identifying different radioisotopes over an energy range from a few keV up to 2 MeV, and useful for efficient characterization of CZT crystals. The detector is built with a 3 x 3 matrix of CZT crystals, each measuring approximately 6 mm x 6 mm x 15 mm. The charge generated within the sensor’s active volume is read out via an anode connected directly to the AVG3_Dev integrated circuit. A current signal induced by charge drift is collected on side pads of the crystals, enabling reconstruction of a 3D interaction position. This paper discusses the design, development, and performance of the standalone, mobile detector system, which integrates the AVG3_Dev readout IC developed at Brookhaven National Laboratory, a high-speed FPGA-based with per-channel digital signal processing, and embedded system capabilities. The device is compact, battery-powered, and supports wireless data streaming, making it suitable for field operations for radioisotope identification.

47 OTHER INSTRUMENTATION↗
DOE OSTI2011

Indirect Estimation of Radioactivity in Containerized Cargo

Detecting illicit nuclear and radiological material in containerized cargo challenges the state of the art in detection systems. Current systems are being evaluated and new systems envisioned to address the need for the high probability of detection and extremely low false alarm rates necessary to thwart potential threats and extremely low nuisance and false alarm rates while maintaining necessary to maintain the flow of commerce impacted by the enormous volume of commodities imported in shipping containers. Maintaining flow of commerce also means that primary inspection must be rapid, requiring relatively indirect measurements of cargo from outside the containers. With increasing information content in such indirect measurements, it is natural to ask how the information might be combined to improved detection. Toward this end, we present an approach to estimating isotopic activity of naturally occurring radioactive material in cargo grouped by commodity type, combining container manifest data with radiography and gamma spectroscopy aligned to location along the container. The heart of this approach is our statistical model of gamma counts within peak regions of interest, which captures the effects of background suppression, counting noise, convolution of neighboring cargo contributions, and down-scattered photons to provide physically constrained estimates of counts due to decay of specific radioisotopes in cargo alone. Coupled to that model, we use a mechanistic model of self-attenuated radiation flux to estimate the isotopic activity within cargo, segmented by location within each container, that produces those counts. We demonstrate our approach by applying it to a set of measurements taken at the Port of Seattle in 2006. This approach to synthesizing disparate available data streams and extraction of cargo characteristics holds the potential to improve primary inspection using current detection capabilities and to enable simulation-based evaluation of new candidate detection systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Seismoacoustic Analysis of Chemical Explosions at the Nevada National Security Site

In recent years, two sets of chemical explosions have been conducted at the Nevada National Security Site (NNSS): 6 explosions from Phase I of the Source Physics Experiment (SPE) and 4 explosions from the Forensics Surface Events (FSE). We have estimated the explosive yield and depth-of-burial/height-of-burst of both from the synthesis of seismic and low-frequency acoustic data. Analysis of the seismic signal is performed using a waveform envelope technique. Using seismic data only, however, there is a tradeoff between the yield and depth or height of the explosion, which becomes especially acute for near-surface events. This tradeoff between yield and depth/height can be broken by including complementary analysis of the acoustic signal using the acoustic waveform inversion method. The acoustic signal also has a strong tradeoff between a yield and depth/height, but the slope is opposite that of the seismic for near-surface events. We use a likelihood function to combine the seismic and acoustic analysis and improve our estimates of yield and depth/height for these sets of explosions. The results are generally consistent with the known parameters, but can be improved upon by higher-frequency seismic analysis and improved acoustic impulse scaling for large scaled depths-of-burial. These events serve as prime examples of data fusion from multiple data streams. The challenge will be to apply the method to events at longer regional distances where the seismic signals will include phases traveling in the upper mantle, and the acoustic signals will be recorded as infrasound signals, which are subject to atmospheric variability.

58 GEOSCIENCES↗
DOE OSTI2022

Comparing Model Representations of Physiological Limits on Transpiration at a Semi-arid Ponderosa Pine Site

Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi-empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi-arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big-leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape

Arctic warming is altering vegetation and carbon dynamics with global implications, yet Earth System Model (ESM) predictions in the Arctic remain highly uncertain, in part due to historically limited data for model parameterization and validation. As such, ESMs typically represent Arctic ecosystems in an oversimplified manner. Recently, nine plant functional types (PFTs) designed to realistically represent tundra vegetation were integrated into the Energy Exascale Earth System Model (E3SM) Land Model (ELM) and parameterized using plot-scale observations from a single site. Additional evaluation was needed to determine their transferability across the Arctic. Here, in this study, we evaluated whether refined representation of tundra vegetation improved model accuracy by conducting spatially explicit 100 × 100 m resolution ELM simulations on Alaska's Seward Peninsula. Simulations with the default two-PFT configuration and with the nine Arctic-specific PFTs were benchmarked against observations of net ecosystem exchange, gross primary production, and aboveground biomass from multiple data streams including an eddy covariance flux tower, flux chambers, and aircraft and unoccupied aerial system hyperspectral remote sensing. Evaluation revealed that Arctic-specific PFT simulations produced more realistic landscape-level carbon exchanges, and better captured observed heterogeneity in biomass and productivity, explaining 60%–70% of spatial variance (R 2 = 0.6–0.7) compared to just 12%–18% (R 2 = 0.12–0.18) with the default configuration. However, the refined model failed to reproduce observed aboveground biomass for highly productive alder-willow communities, requiring further evaluation of carbon allocation parameterizations for tall shrubs that are increasingly expanding across tundra landscapes. Our results demonstrate that enhanced representation of vegetation heterogeneity boosts predictive understanding of tundra carbon dynamics, facilitating regional to pan-Arctic model and remote-sensing scaling.

Murphy, Bailey A. [Oak Ridge National Laboratory (↗
DOE OSTI2021

Ensemble learning-iterative training machine learning for uncertainty quantification and automated experiment in atom-resolved microscopy

Deep learning has emerged as a technique of choice for rapid feature extraction across imaging disciplines, allowing rapid conversion of the data streams to spatial or spatiotemporal arrays of features of interest. However, applications of deep learning in experimental domains are often limited by the out-of-distribution drift between the experiments, where the network trained for one set of imaging conditions becomes sub-optimal for different ones. This limitation is particularly stringent in the quest to have an automated experiment setting, where retraining or transfer learning becomes impractical due to the need for human intervention and associated latencies. Here we explore the reproducibility of deep learning for feature extraction in atom-resolved electron microscopy and introduce workflows based on ensemble learning and iterative training to greatly improve feature detection. This approach allows incorporating uncertainty quantification into the deep learning analysis and also enables rapid automated experimental workflows where retraining of the network to compensate for out-of-distribution drift due to subtle change in imaging conditions is substituted for human operator or programmatic selection of networks from the ensemble. This methodology can be further applied to machine learning workflows in other imaging areas including optical and chemical imaging.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ultrafast Bragg coherent diffraction imaging of epitaxial thin films using deep complex-valued neural networks

Abstract Domain wall structures form spontaneously due to epitaxial misfit during thin film growth. Imaging the dynamics of domains and domain walls at ultrafast timescales can provide fundamental clues to features that impact electrical transport in electronic devices. Recently, deep learning based methods showed promising phase retrieval (PR) performance, allowing intensity-only measurements to be transformed into snapshot real space images. While the Fourier imaging model involves complex-valued quantities, most existing deep learning based methods solve the PR problem with real-valued based models, where the connection between amplitude and phase is ignored. To this end, we involve complex numbers operation in the neural network to preserve the amplitude and phase connection. Therefore, we employ the complex-valued neural network for solving the PR problem and evaluate it on Bragg coherent diffraction data streams collected from an epitaxial La 2-x Sr x CuO 4 (LSCO) thin film using an X-ray Free Electron Laser (XFEL). Our proposed complex-valued neural network based approach outperforms the traditional real-valued neural network methods in both supervised and unsupervised learning manner. Phase domains are also observed from the LSCO thin film at an ultrafast timescale using the complex-valued neural network.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

California wildfire spread derived using VIIRS satellite observations and an object-based tracking system

Changing wildfire regimes in the western US and other fire-prone regions pose considerable risks to human health and ecosystem function. However, our understanding of wildfire behavior is still limited by a lack of data products that systematically quantify fire spread, behavior and impacts. Here we develop a novel object-based system for tracking the progression of individual fires using 375 m Visible Infrared Imaging Radiometer Suite active fire detections. At each half-daily time step, fire pixels are clustered according to their spatial proximity, and are either appended to an existing active fire object or are assigned to a new object. This automatic system allows us to update the attributes of each fire event, delineate the fire perimeter, and identify the active fire front shortly after satellite data acquisition. Using this system, we mapped the history of California fires during 2012–2020. Our approach and data stream may be useful for calibration and evaluation of fire spread models, estimation of near-real-time wildfire emissions, and as means for prescribing initial conditions in fire forecast models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Optimal strategy for polarization modulation in the LSPE-SWIPE experiment

Context. Cosmic microwave background (CMB) B-mode experiments are required to control systematic effects with an unprecedented level of accuracy. Polarization modulation by a half wave plate (HWP) is a powerful technique able to mitigate a large number of the instrumental systematics. Aims. Our goal is to optimize the polarization modulation strategy of the upcoming LSPE-SWIPE balloon-borne experiment, devoted to the accurate measurement of CMB polarization at large angular scales. Methods. We departed from the nominal LSPE-SWIPE modulation strategy (HWP stepped every 60 s with a telescope scanning at around 12 deg/s) and performed a thorough investigation of a wide range of possible HWP schemes (either in stepped or continuously spinning mode and at different azimuth telescope scan-speeds) in the frequency, map and angular power spectrum domain. In addition, we probed the effect of high-pass and band-pass filters of the data stream and explored the HWP response in the minimal case of one detector for one operation day (critical for the single-detector calibration process). We finally tested the modulation performance against typical HWP-induced systematics. Results. Our analysis shows that some stepped HWP schemes, either slowly rotating or combined with slow telescope modulations, represent poor choices. Moreover, our results point out that the nominal configuration may not be the most convenient choice. While a large class of spinning designs provides comparable results in terms of pixel angle coverage, map-making residuals and BB power spectrum standard deviations with respect to the nominal strategy, we find that some specific configurations (e.g., a rapidly spinning HWP with a slow gondola modulation) allow a more efficient polarization recovery in more general real-case situations. Conclusions. Although our simulations are specific to the LSPE-SWIPE mission, the general outcomes of our analysis can be easily generalized to other CMB polarization experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

DUNE DAQ R&D integration in ProtoDUNE Single-Phase at CERN

The DAQ system of ProtoDUNE-SP successfully proved its design principles and met the requirements of the beam run of 2018. The technical design of the DAQ system for the DUNE experiment has major differences compared to the prototype due to different requirements placed on the detector, as well as a radically different location of operation. The single-phase prototype at CERN is a major integration facility for R&D aspects of the DUNE DAQ system. The facility allows for the exploration of additional data processing capabilities and optimization of the FELIX system, which is the chosen TPC readout solution for the DUNE single-phase detectors. One of the fundamental differences from the prototype is that the DUNE DAQ relies on self-triggering. Therefore, real-time processing of the data stream for hit and trigger primitive finding is essential for the requirement of continuous readout. The supernova burst trigger requires a large and fast buffering technique, where 3D XPoint persistent memory solutions are evaluated and integrated. In order to maximize resource utilization of the FELIX hosting servers, the elimination of the 100 Gb network communication stack is desired. This implies the design and development of a single-host application layer, which is a fundamental element of the self-triggering chain. This paper discusses the evaluation and integration of these developments for the DUNE DAQ, in the ProtoDUNE environment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

HOSS!

The Hall-D Online Skim System (HOSS) was developed to simultaneously solve two issues for the high intensity GlueX experiment. One was to parallelize the writing of raw data files to disk in order to improve bandwidth. The other was to distribute the raw data across multiple compute nodes in order to produce calibration skims of the data online. The highly configurable system employs RDMA, RAM disks, and zeroMQ driven by Python to simultaneously store and process the full high intensity GlueX data stream.

Lawrence, David↗
DOE OSTI2014

A strained silicon cold electron bolometer using Schottky contacts

We describe optical characterisation of a strained silicon cold electron bolometer (CEB), operating on a 350 mK stage, designed for absorption of millimetre-wave radiation. The silicon cold electron bolometer utilises Schottky contacts between a superconductor and an n{sup ++} doped silicon island to detect changes in the temperature of the charge carriers in the silicon, due to variations in absorbed radiation. By using strained silicon as the absorber, we decrease the electron-phonon coupling in the device and increase the responsivity to incoming power. The strained silicon absorber is coupled to a planar aluminium twin-slot antenna designed to couple to 160 GHz and that serves as the superconducting contacts. From the measured optical responsivity and spectral response, we calculate a maximum optical efficiency of 50% for radiation coupled into the device by the planar antenna and an overall noise equivalent power, referred to absorbed optical power, of 1.1×10{sup −16} W Hz{sup −1/2} when the detector is observing a 300 K source through a 4 K throughput limiting aperture. Even though this optical system is not optimized, we measure a system noise equivalent temperature difference of 6 mK Hz{sup −1/2}. We measure the noise of the device using a cross-correlation of time stream data, measured simultaneously with two junction field-effect transistor amplifiers, with a base correlated noise level of 300 pV Hz{sup −1/2} and find that the total noise is consistent with a combination of photon noise, current shot noise, and electron-phonon thermal noise.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Note: Design of a full photon-timing recorder down to 1-ns resolution for fluorescence fluctuation measurements

A photon timing recorder was realized in a field programmable gate array to capture all timing data of photons on multiple channels with down to a 1-ns resolution and to transfer all data to a host computer in real-time through universal serial bus with more than 10 M events/s transfer rate. The main concept is that photon time series can be regarded as a serial communication data stream. This recorder was successfully applied for simultaneous measurements of fluorescence fluctuation and lifetime of near-infrared dyes in solution. This design is not only limited to the fluorescence fluctuation measurement but also applicable to any kind of photon counting experiments in a nanosecond time range because of the simple and easily modifiable design.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗